A methodology for spatial distribution of grain and voids in self compacting concrete using digital image processing methods

ÖNAL O., Oezden G., FELEKOĞLU B.

COMPUTERS AND CONCRETE, cilt.5, sa.1, ss.61-74, 2008 (SCI-Expanded) identifier identifier

  • Yayın Türü: Makale / Tam Makale
  • Cilt numarası: 5 Sayı: 1
  • Basım Tarihi: 2008
  • Doi Numarası: 10.12989/cac.2008.5.1.061
  • Dergi Adı: COMPUTERS AND CONCRETE
  • Derginin Tarandığı İndeksler: Science Citation Index Expanded (SCI-EXPANDED), Scopus
  • Sayfa Sayıları: ss.61-74
  • Anahtar Kelimeler: digital image processing algorithms, grain characteristics, segregation, void distribution, segmentation, watershed, PARTICLE-SIZE DISTRIBUTION, THIN-SECTIONS, QUANTIFICATION, SEGMENTATION, PERMEABILITY, SOILS, SHAPE
  • Dokuz Eylül Üniversitesi Adresli: Evet

Özet

Digital image processing algorithms for the analysis and characterization of grains and voids in cemented materials were developed using toolbox functions of a mathematical software package. Utilization of grayscale, color and watershed segmentation algorithms and their performances were demonstrated on artificially prepared self-compacting concrete (SCC) samples. It has been found that color segmentation was more advantageous over the gray scale segmentation for the detection of voids whereas the latter method provided satisfying results for the aggregate grains due to the sharp contrast between their colors and the cohesive matrix. The watershed segmentation method, on the other hand, appeared to be very efficient while separating touching objects in digital images.